Premium bidding of online advertisements

Abstract

The subject matter disclosed herein relates to utilizing one or more premium rules to associate a premium markup to a base bid for online advertising.

1 . A method comprising:
 with at least one computing platform:   receiving advertising data associating an online advertising budget among one or more ad units in a hierarchical node structure, wherein at least one ad unit comprises a keyword term and a creative component;   receiving advertising data associating one or more premium rules with one or more nodes of said hierarchical node structure, wherein said one or more premium rules comprise a hierarchical target node structure comprising two or more target dimensions;   accessing base bid data associated with a node of said hierarchical node structure, wherein said node is associated with at least a portion of said at least one ad unit; and   determining premium markup data based at least in part on said one or more premium rules comparing a current context associated with a given end user to said two or more target dimensions.   
     
     
         2 . The method of  claim 1 , wherein said two or more premium rules are associated to said at least one ad unit at one or more of the following hierarchical nodes: an account-type node, a campaign-type node, and/or an ad-group-type node. 
     
     
         3 . The method of  claim 1 , wherein said node comprises a keyword-term-type node associated with a keyword term portion of said at least one ad unit. 
     
     
         4 . The method of  claim 1 , wherein said node comprises an ad-group-type node associated with said at least one ad unit. 
     
     
         5 . The method of  claim 1 , wherein at least one of said target dimensions is associated with one or more of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, and/or publication site. 
     
     
         6 . The method of  claim 1 , wherein said hierarchical target node structure of two or more target dimensions comprises one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension, wherein said first and second target dimensions are restrained so that said comparison of a current context to said two or more target dimensions will match no more than one of said one or more target nodes associated with said first target dimension and no more than one of said one or more target nodes associated with said second target dimension. 
     
     
         7 . The method of  claim 1 , wherein said premium markup data is based at least in part on a percentage of said base bid data. 
     
     
         8 . The method of  claim 1 , further comprising preventing a group of two or more premium rules from reusing identical target dimension sets, wherein one or more of said target dimensions comprise a target dimension portion. 
     
     
         9 . The method of  claim 1 , further comprising determining total bid data based at least in part on said premium markup data and said base bid data. 
     
     
         10 . The method of  claim 1 , further comprising:
 determining total bid data based at least in part on said premium markup data and said base bid data;   wherein said two or more premium rules are associated with said at least one ad unit at one or more of the following hierarchical nodes: an account-type node, a campaign-type node, and/or an ad-group-type node;   wherein said target dimensions are associated with one or more of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, and/or publication site;   preventing a group of two or more premium rules from reusing identical target dimension sets, wherein one or more of said target dimensions comprise a target dimension portion; and   wherein said hierarchical target node structure of two or more target dimensions comprises one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension, wherein said first and second target dimensions are restrained so that said comparison of a current context to said two or more target dimensions will match no more than one of said one or more target nodes associated with said first target dimension and no more than one of said one or more target nodes associated with said second target dimension.   
     
     
         11 . An article comprising:
 a storage medium comprising machine-readable instructions stored thereon, which, if executed by one or more processing units, operatively enable a computing platform to:
 receive advertising data that associates an online advertising budget among one or more ad units in a hierarchical node structure, wherein at least one ad unit comprises a keyword term and a creative component; 
 receive advertising data that associates one or more premium rules with one or more nodes of said hierarchical node structure, wherein said one or more premium rules comprise a hierarchical target node structure comprising two or more target dimensions; 
 access base bid data associated with a node of said hierarchical node structure, wherein said leaf node is associated with at least a portion of at least one of said ad units; and 
 determine premium markup data based at least in part on a comparison via said one or more premium rules of a current context associated with a given end user to said two or more target dimensions. 
   
     
     
         12 . The article of  claim 11 , wherein said two or more premium rules are associated to said at least one of said ad units at one or more of the following hierarchical nodes: an account-type node, a campaign-type node, and/or an ad-group-type node. 
     
     
         13 . The article of  claim 11 , wherein at least one of said target dimensions is associated with one or more of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, and/or publication site. 
     
     
         14 . The article of  claim 11 , wherein said hierarchical target node structure of two or more target dimensions comprises one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension, wherein said first and second target dimensions are restrained so that said comparison of a current context to said two or more target dimensions will match no more than one of said one or more target nodes associated with said first target dimension and no more than one of said one or more target nodes associated with said second target dimension. 
     
     
         15 . The article of  claim 11 , wherein said machine-readable instructions, if executed by the one or more processing units, operatively enable the computing platform to:
 determine total bid data based at least in part on said premium markup data with said base bid data.   
     
     
         16 . An apparatus comprising:
 a computing platform, said computing platform being operatively enabled to:   receive advertising data that associates an online advertising budget among one or more ad units in a hierarchical node structure, wherein at least one ad unit comprises a keyword term and a creative component;   receive advertising data that associates one or more premium rules with one or more nodes of said hierarchical node structure, wherein said one or more premium rules comprise a hierarchical target node structure comprising two or more target dimensions;   access base bid data associated with a node of said hierarchical node structure, wherein said node is associated with at least a portion of at least one of said ad units; and   determine premium markup data based at least in part on a comparison via said one or more premium rules of a current context associated with a given end user to said two or more target dimensions.   
     
     
         17 . The apparatus of  claim 16 , wherein said two or more premium rules are associated to said at least one of said ad units at one or more of the following hierarchical nodes: an account-type node, a campaign-type node, and/or an ad-group-type node. 
     
     
         18 . The apparatus of  claim 16 , wherein said target dimensions are associated with one or more of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, and/or publication site. 
     
     
         19 . The apparatus of  claim 16 , wherein said hierarchical target node structure of two or more target dimensions comprises one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension, wherein said first and second target dimensions are restrained so that said comparison of a current context to said two or more target dimensions will match no more than one of said one or more target nodes associated with said first target dimension and no more than one of said one or more target nodes associated with said second target dimension. 
     
     
         20 . The apparatus of  claim 16 , wherein said machine-readable instructions, if executed by a computing platform, further direct a computing platform to determine total bid data based at least in part on said premium markup data and said base bid data.